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train | HyperbandSearchManager.should_reduce_configs | Return a boolean to indicate if we need to reschedule another bracket iteration. | polyaxon/hpsearch/search_managers/hyperband.py | def should_reduce_configs(self, iteration, bracket_iteration):
"""Return a boolean to indicate if we need to reschedule another bracket iteration."""
n_configs_to_keep = self.get_n_config_to_keep_for_iteration(
iteration=iteration, bracket_iteration=bracket_iteration)
return n_config... | def should_reduce_configs(self, iteration, bracket_iteration):
"""Return a boolean to indicate if we need to reschedule another bracket iteration."""
n_configs_to_keep = self.get_n_config_to_keep_for_iteration(
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train | validate_resource | Validates a resource | polyaxon/libs/resource_validation.py | def validate_resource(resource) -> None:
"""Validates a resource"""
if resource is not None and not isinstance(resource, dict):
raise ValidationError('The resource is not valid.')
if isinstance(resource, dict) and set(resource.keys()) <= {'requests', 'limits'}:
raise ValidationError(
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"""Validates a resource"""
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raise ValidationError('The resource is not valid.')
if isinstance(resource, dict) and set(resource.keys()) <= {'requests', 'limits'}:
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train | ResourceManager.get_init_container | Pod init container for setting outputs path. | polyaxon/scheduler/spawners/templates/experiment_jobs/manager.py | def get_init_container(self,
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env_vars,
context_mounts,
persistence_outputs,
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train | RepoMixin.path | We need to nest the git path inside the project path to make it easier
to create docker images. | polyaxon/db/models/repos.py | def path(self) -> str:
"""We need to nest the git path inside the project path to make it easier
to create docker images."""
return os.path.join(self.project_path, self.project.name) | def path(self) -> str:
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train | RepoMixin.last_commit | Returns a tuple (hash, and commit object) | polyaxon/db/models/repos.py | def last_commit(self) -> Tuple:
"""Returns a tuple (hash, and commit object)"""
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return git.get_last_commit(repo_path=self.path) | def last_commit(self) -> Tuple:
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train | TensorboardSpawner.validate_stores_secrets_keys | Validates that we can only authenticate to one S3 and one GCS. | polyaxon/scheduler/spawners/tensorboard_spawner.py | def validate_stores_secrets_keys(stores_secrets):
"""Validates that we can only authenticate to one S3 and one GCS."""
stores = set([])
for store_secret in stores_secrets:
if store_secret['store'] in stores:
raise TensorboardValidation('Received an invalid store confi... | def validate_stores_secrets_keys(stores_secrets):
"""Validates that we can only authenticate to one S3 and one GCS."""
stores = set([])
for store_secret in stores_secrets:
if store_secret['store'] in stores:
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train | TensorboardSpawner.get_stores_secrets_volumes | Handles the case of GCS and S3 and create a volume with secret file. | polyaxon/scheduler/spawners/tensorboard_spawner.py | def get_stores_secrets_volumes(cls, stores_secrets):
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volumes = []
volume_mounts = []
for store_secret in stores_secrets:
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volumes = []
volume_mounts = []
for store_secret in stores_secrets:
store = store_secret['store']
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train | TensorboardSpawner.get_stores_secrets_command_args | Create an auth command for S3 and GCS. | polyaxon/scheduler/spawners/tensorboard_spawner.py | def get_stores_secrets_command_args(cls, stores_secrets):
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commands = []
for store_secret in stores_secrets:
store = store_secret['store']
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store = store_secret['store']
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train | RedisEphemeralTokens.make_token | Returns a token to be used x number of times to allow a user account to access
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Returns a token to be used x number of times to allow a user account to access
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"""
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train | RedisEphemeralTokens.check_token | Check that a token is correct for a given scope token. | polyaxon/db/redis/ephemeral_tokens.py | def check_token(self, token: 'RedisEphemeralTokens') -> bool:
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train | UtilityFunction.max_compute | A function to find the maximum of the acquisition function
It uses a combination of random sampling (cheap) and the 'L-BFGS-B' optimization method.
First by sampling `n_warmup` (1e5) points at random,
and then running L-BFGS-B from `n_iter` (250) random starting points.
Params:
... | polyaxon/hpsearch/search_managers/bayesian_optimization/acquisition_function.py | def max_compute(self, y_max, bounds, n_warmup=100000, n_iter=250):
"""A function to find the maximum of the acquisition function
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and then runnin... | def max_compute(self, y_max, bounds, n_warmup=100000, n_iter=250):
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train | OrderingFilter.get_ordering | Ordering is set by a comma delimited ?ordering=... query parameter.
The `ordering` query parameter can be overridden by setting
the `ordering_param` value on the OrderingFilter or by
specifying an `ORDERING_PARAM` value in the API settings. | polyaxon/api/filters.py | def get_ordering(self, request, queryset, view):
"""
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the `ordering_param` value on the OrderingFilter or by
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train | ResourceManager.get_init_container | Pod init container for setting outputs path. | polyaxon/scheduler/spawners/templates/notebooks/manager.py | def get_init_container(self,
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train | RegistrationView.get_activation_key | Generate the activation key which will be emailed to the user. | polyaxon/api/users/views.py | def get_activation_key(self, user):
"""
Generate the activation key which will be emailed to the user.
"""
return signing.dumps(
obj=getattr(user, user.USERNAME_FIELD),
salt=self.key_salt
) | def get_activation_key(self, user):
"""
Generate the activation key which will be emailed to the user.
"""
return signing.dumps(
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salt=self.key_salt
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train | RegistrationView.send_activation_email | Send the activation email. The activation key is the username,
signed using TimestampSigner. | polyaxon/api/users/views.py | def send_activation_email(self, user):
"""
Send the activation email. The activation key is the username,
signed using TimestampSigner.
"""
activation_key = self.get_activation_key(user)
context = self.get_email_context(activation_key)
context.update({
... | def send_activation_email(self, user):
"""
Send the activation email. The activation key is the username,
signed using TimestampSigner.
"""
activation_key = self.get_activation_key(user)
context = self.get_email_context(activation_key)
context.update({
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train | SimpleRegistrationView.create_inactive_user | Create the inactive user account and wait for validation from superuser | polyaxon/api/users/views.py | def create_inactive_user(self, form):
"""Create the inactive user account and wait for validation from superuser"""
new_user = form.save(commit=False)
new_user.is_active = False
new_user.save()
return new_user | def create_inactive_user(self, form):
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new_user = form.save(commit=False)
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new_user.save()
return new_user | [
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train | ActivationView.validate_key | Verify that the activation key is valid and within the
permitted activation time window, returning the username if
valid or ``None`` if not. | polyaxon/api/users/views.py | def validate_key(self, activation_key):
"""
Verify that the activation key is valid and within the
permitted activation time window, returning the username if
valid or ``None`` if not.
"""
try:
username = signing.loads(
activation_key,
... | def validate_key(self, activation_key):
"""
Verify that the activation key is valid and within the
permitted activation time window, returning the username if
valid or ``None`` if not.
"""
try:
username = signing.loads(
activation_key,
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train | ActivationView.get_user | Given the verified username, look up and return the
corresponding user account if it exists, or ``None`` if it
doesn't. | polyaxon/api/users/views.py | def get_user(self, username):
"""
Given the verified username, look up and return the
corresponding user account if it exists, or ``None`` if it
doesn't.
"""
User = get_user_model() # noqa
try:
user = User.objects.get(**{
User.USERNAM... | def get_user(self, username):
"""
Given the verified username, look up and return the
corresponding user account if it exists, or ``None`` if it
doesn't.
"""
User = get_user_model() # noqa
try:
user = User.objects.get(**{
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train | ActivationView.get | The base activation logic; subclasses should leave this method
alone and implement activate(), which is called from this method. | polyaxon/api/users/views.py | def get(self, request, *args, **kwargs):
"""The base activation logic; subclasses should leave this method
alone and implement activate(), which is called from this method.
"""
activated_user = self.activate(*args, **kwargs)
if activated_user:
users_signals.user_activ... | def get(self, request, *args, **kwargs):
"""The base activation logic; subclasses should leave this method
alone and implement activate(), which is called from this method.
"""
activated_user = self.activate(*args, **kwargs)
if activated_user:
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train | BaseResourceManager.get_pod_container | Pod job container for task. | polyaxon/scheduler/spawners/templates/resource_manager.py | def get_pod_container(self,
volume_mounts,
persistence_outputs=None,
persistence_data=None,
outputs_refs_jobs=None,
outputs_refs_experiments=None,
secret_refs=None,... | def get_pod_container(self,
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persistence_data=None,
outputs_refs_jobs=None,
outputs_refs_experiments=None,
secret_refs=None,... | [
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train | BaseResourceManager.get_sidecar_container | Pod sidecar container for task logs. | polyaxon/scheduler/spawners/templates/resource_manager.py | def get_sidecar_container(self, volume_mounts):
"""Pod sidecar container for task logs."""
return get_sidecar_container(
job_container_name=self.job_container_name,
sidecar_container_name=self.sidecar_container_name,
sidecar_docker_image=self.sidecar_docker_image,
... | def get_sidecar_container(self, volume_mounts):
"""Pod sidecar container for task logs."""
return get_sidecar_container(
job_container_name=self.job_container_name,
sidecar_container_name=self.sidecar_container_name,
sidecar_docker_image=self.sidecar_docker_image,
... | [
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train | BaseResourceManager.get_task_pod_spec | Pod spec to be used to create pods for tasks: master, worker, ps. | polyaxon/scheduler/spawners/templates/resource_manager.py | def get_task_pod_spec(self,
volume_mounts,
volumes,
resource_name,
persistence_outputs=None,
persistence_data=None,
outputs_refs_jobs=None,
... | def get_task_pod_spec(self,
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outputs_refs_jobs=None,
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train | IdentityWizard.validate_username | This validation step is done when we are sure the user
does not exit on the systems and we need to create a new user. | polyaxon/sso/wizard.py | def validate_username(username):
"""
This validation step is done when we are sure the user
does not exit on the systems and we need to create a new user.
"""
try:
validate_slug(username)
except ValidationError:
username = slugify(username)
... | def validate_username(username):
"""
This validation step is done when we are sure the user
does not exit on the systems and we need to create a new user.
"""
try:
validate_slug(username)
except ValidationError:
username = slugify(username)
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train | Action._prepare | This is where you should alter the context to fit the action.
Default behaviour will leave the context as it is. | polyaxon/action_manager/action.py | def _prepare(cls, context: Dict) -> Dict:
"""This is where you should alter the context to fit the action.
Default behaviour will leave the context as it is.
"""
if not context and cls.raise_empty_context:
raise PolyaxonActionException('{} received invalid payload context.'.... | def _prepare(cls, context: Dict) -> Dict:
"""This is where you should alter the context to fit the action.
Default behaviour will leave the context as it is.
"""
if not context and cls.raise_empty_context:
raise PolyaxonActionException('{} received invalid payload context.'.... | [
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train | copy_experiment | If experiment is a restart, we should resume from last check point | polyaxon/scheduler/tasks/experiments.py | def copy_experiment(experiment):
"""If experiment is a restart, we should resume from last check point"""
try:
publisher.publish_experiment_job_log(
log_lines='Copying outputs from experiment `{}` into experiment `{}`'.format(
experiment.original_experiment.unique_name, exper... | def copy_experiment(experiment):
"""If experiment is a restart, we should resume from last check point"""
try:
publisher.publish_experiment_job_log(
log_lines='Copying outputs from experiment `{}` into experiment `{}`'.format(
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train | EventService.record | Validate and record an event.
>>> record('event.action', object_instance) | polyaxon/event_manager/event_service.py | def record(self,
event_type: str,
event_data: Mapping = None,
instance: Any = None,
**kwargs) -> 'Event':
""" Validate and record an event.
>>> record('event.action', object_instance)
"""
if not self.is_setup:
retur... | def record(self,
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>>> record('event.action', object_instance)
"""
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train | generate | Build necessary code for a job to run | polyaxon/dockerizer/dockerizer/initializer/generate.py | def generate(job,
build_path: str,
from_image: str,
build_steps: Optional[List[str]] = None,
env_vars: Optional[List[Tuple[str, str]]] = None,
nvidia_bin: str = None,
set_lang_env: bool = True,
uid: int = None,
gid: ... | def generate(job,
build_path: str,
from_image: str,
build_steps: Optional[List[str]] = None,
env_vars: Optional[List[Tuple[str, str]]] = None,
nvidia_bin: str = None,
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uid: int = None,
gid: ... | [
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train | RandomSearchManager.get_suggestions | Return a list of suggestions based on random search.
Params:
matrix: `dict` representing the {hyperparam: hyperparam matrix config}.
n_suggestions: number of suggestions to make. | polyaxon/hpsearch/search_managers/random.py | def get_suggestions(self, iteration_config=None):
"""Return a list of suggestions based on random search.
Params:
matrix: `dict` representing the {hyperparam: hyperparam matrix config}.
n_suggestions: number of suggestions to make.
"""
matrix = self.hptuning_conf... | def get_suggestions(self, iteration_config=None):
"""Return a list of suggestions based on random search.
Params:
matrix: `dict` representing the {hyperparam: hyperparam matrix config}.
n_suggestions: number of suggestions to make.
"""
matrix = self.hptuning_conf... | [
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train | ExperimentMetricListView.get_serializer | if an array is passed, set serializer to many | polyaxon/api/experiments/views.py | def get_serializer(self, *args, **kwargs):
""" if an array is passed, set serializer to many """
if isinstance(kwargs.get('data', {}), list):
kwargs['many'] = True
return super().get_serializer(*args, **kwargs) | def get_serializer(self, *args, **kwargs):
""" if an array is passed, set serializer to many """
if isinstance(kwargs.get('data', {}), list):
kwargs['many'] = True
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train | logs_handle_experiment_job | Task handling for sidecars logs. | polyaxon/logs_handlers/tasks/log_handlers.py | def logs_handle_experiment_job(experiment_name: str,
experiment_uuid: str,
log_lines: Optional[Union[str, Iterable[str]]],
temp: bool = True) -> None:
"""Task handling for sidecars logs."""
handle_experiment_job_log(exp... | def logs_handle_experiment_job(experiment_name: str,
experiment_uuid: str,
log_lines: Optional[Union[str, Iterable[str]]],
temp: bool = True) -> None:
"""Task handling for sidecars logs."""
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train | logs_handle_job | Task handling for sidecars logs. | polyaxon/logs_handlers/tasks/log_handlers.py | def logs_handle_job(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]],
temp: bool = True) -> None:
"""Task handling for sidecars logs."""
handle_job_logs(job_uuid=job_uuid,
job_name=job_name,
... | def logs_handle_job(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]],
temp: bool = True) -> None:
"""Task handling for sidecars logs."""
handle_job_logs(job_uuid=job_uuid,
job_name=job_name,
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train | logs_handle_build_job | Task handling for sidecars logs. | polyaxon/logs_handlers/tasks/log_handlers.py | def logs_handle_build_job(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]],
temp: bool = True) -> None:
"""Task handling for sidecars logs."""
handle_build_job_logs(job_uuid=job_uuid,
... | def logs_handle_build_job(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]],
temp: bool = True) -> None:
"""Task handling for sidecars logs."""
handle_build_job_logs(job_uuid=job_uuid,
... | [
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train | HyperbandIterationManager.create_iteration | Create an iteration for the experiment group. | polyaxon/hpsearch/iteration_managers/hyperband.py | def create_iteration(self, num_suggestions=0):
"""Create an iteration for the experiment group."""
from db.models.experiment_groups import ExperimentGroupIteration
search_manager = self.experiment_group.search_manager
iteration_config = self.experiment_group.iteration_config
if... | def create_iteration(self, num_suggestions=0):
"""Create an iteration for the experiment group."""
from db.models.experiment_groups import ExperimentGroupIteration
search_manager = self.experiment_group.search_manager
iteration_config = self.experiment_group.iteration_config
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train | HyperbandIterationManager.get_reduced_configs | Reduce the experiments to restart. | polyaxon/hpsearch/iteration_managers/hyperband.py | def get_reduced_configs(self):
"""Reduce the experiments to restart."""
iteration_config = self.experiment_group.iteration_config
if iteration_config is None:
logger.error(
'Experiment group `%s` attempt to update iteration, but has no iteration',
self... | def get_reduced_configs(self):
"""Reduce the experiments to restart."""
iteration_config = self.experiment_group.iteration_config
if iteration_config is None:
logger.error(
'Experiment group `%s` attempt to update iteration, but has no iteration',
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train | HyperbandIterationManager.reduce_configs | Reduce the experiments to restart. | polyaxon/hpsearch/iteration_managers/hyperband.py | def reduce_configs(self):
"""Reduce the experiments to restart."""
experiment_ids = self.get_reduced_configs()
experiments = self.experiment_group.experiments.filter(id__in=experiment_ids)
self.create_iteration()
iteration_config = self.experiment_group.iteration_config
h... | def reduce_configs(self):
"""Reduce the experiments to restart."""
experiment_ids = self.get_reduced_configs()
experiments = self.experiment_group.experiments.filter(id__in=experiment_ids)
self.create_iteration()
iteration_config = self.experiment_group.iteration_config
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train | Project.all_experiment_groups | Similar to experiment_groups,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/projects.py | def all_experiment_groups(self):
"""
Similar to experiment_groups,
but uses the default manager to return archived experiments as well.
"""
from db.models.experiment_groups import ExperimentGroup
return ExperimentGroup.all.filter(project=self) | def all_experiment_groups(self):
"""
Similar to experiment_groups,
but uses the default manager to return archived experiments as well.
"""
from db.models.experiment_groups import ExperimentGroup
return ExperimentGroup.all.filter(project=self) | [
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train | Project.all_jobs | Similar to jobs,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/projects.py | def all_jobs(self):
"""
Similar to jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.jobs import Job
return Job.all.filter(project=self) | def all_jobs(self):
"""
Similar to jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.jobs import Job
return Job.all.filter(project=self) | [
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train | Project.all_build_jobs | Similar to build_jobs,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/projects.py | def all_build_jobs(self):
"""
Similar to build_jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.build_jobs import BuildJob
return BuildJob.all.filter(project=self) | def all_build_jobs(self):
"""
Similar to build_jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.build_jobs import BuildJob
return BuildJob.all.filter(project=self) | [
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train | Project.all_notebook_jobs | Similar to notebook_jobs,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/projects.py | def all_notebook_jobs(self):
"""
Similar to notebook_jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.notebooks import NotebookJob
return NotebookJob.all.filter(project=self) | def all_notebook_jobs(self):
"""
Similar to notebook_jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.notebooks import NotebookJob
return NotebookJob.all.filter(project=self) | [
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train | Project.all_tensorboard_jobs | Similar to tensorboard_jobs,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/projects.py | def all_tensorboard_jobs(self):
"""
Similar to tensorboard_jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.tensorboards import TensorboardJob
return TensorboardJob.all.filter(project=self) | def all_tensorboard_jobs(self):
"""
Similar to tensorboard_jobs,
but uses the default manager to return archived experiments as well.
"""
from db.models.tensorboards import TensorboardJob
return TensorboardJob.all.filter(project=self) | [
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train | ExperimentGroup.all_experiments | Similar to experiments,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/experiment_groups.py | def all_experiments(self):
"""
Similar to experiments,
but uses the default manager to return archived experiments as well.
"""
from db.models.experiments import Experiment
return Experiment.all.filter(experiment_group=self) | def all_experiments(self):
"""
Similar to experiments,
but uses the default manager to return archived experiments as well.
"""
from db.models.experiments import Experiment
return Experiment.all.filter(experiment_group=self) | [
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train | ExperimentGroup.all_group_experiments | Similar to group_experiments,
but uses the default manager to return archived experiments as well. | polyaxon/db/models/experiment_groups.py | def all_group_experiments(self):
"""
Similar to group_experiments,
but uses the default manager to return archived experiments as well.
"""
from db.models.experiments import Experiment
if self.is_selection:
return Experiment.all.filter(selections=self)
... | def all_group_experiments(self):
"""
Similar to group_experiments,
but uses the default manager to return archived experiments as well.
"""
from db.models.experiments import Experiment
if self.is_selection:
return Experiment.all.filter(selections=self)
... | [
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train | get_dag | Return a dag representation of the nodes passed.
This is equally used for pipelines and pipeline runs.
Params:
nodes: an instance of `Operation` | `OperationRun` the nodes to represent en dag.
downstream_fn: a function that returns the downstream nodes of the a node.
Returns:
tup... | polyaxon/pipelines/dags.py | def get_dag(nodes, downstream_fn) -> Tuple[Dict, Dict]:
"""Return a dag representation of the nodes passed.
This is equally used for pipelines and pipeline runs.
Params:
nodes: an instance of `Operation` | `OperationRun` the nodes to represent en dag.
downstream_fn: a function that returns... | def get_dag(nodes, downstream_fn) -> Tuple[Dict, Dict]:
"""Return a dag representation of the nodes passed.
This is equally used for pipelines and pipeline runs.
Params:
nodes: an instance of `Operation` | `OperationRun` the nodes to represent en dag.
downstream_fn: a function that returns... | [
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train | get_independent_nodes | Get a list of all node in the graph with no dependencies. | polyaxon/pipelines/dags.py | def get_independent_nodes(dag):
"""Get a list of all node in the graph with no dependencies."""
nodes = set(dag.keys())
dependent_nodes = set([node for downstream_nodes in dag.values() for node in downstream_nodes])
return set(nodes - dependent_nodes) | def get_independent_nodes(dag):
"""Get a list of all node in the graph with no dependencies."""
nodes = set(dag.keys())
dependent_nodes = set([node for downstream_nodes in dag.values() for node in downstream_nodes])
return set(nodes - dependent_nodes) | [
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train | get_orphan_nodes | Get orphan nodes for given dag. | polyaxon/pipelines/dags.py | def get_orphan_nodes(dag):
"""Get orphan nodes for given dag."""
independent_nodes = get_independent_nodes(dag)
return set([node for node in independent_nodes if not dag[node]]) | def get_orphan_nodes(dag):
"""Get orphan nodes for given dag."""
independent_nodes = get_independent_nodes(dag)
return set([node for node in independent_nodes if not dag[node]]) | [
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train | has_dependencies | Checks if the node has dependencies. | polyaxon/pipelines/dags.py | def has_dependencies(node, dag):
"""Checks if the node has dependencies."""
for downstream_nodes in dag.values():
if node in downstream_nodes:
return True
return False | def has_dependencies(node, dag):
"""Checks if the node has dependencies."""
for downstream_nodes in dag.values():
if node in downstream_nodes:
return True
return False | [
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train | sort_topologically | Sort the dag breath first topologically.
Only the nodes inside the dag are returned, i.e. the nodes that are also keys.
Returns:
a topological ordering of the DAG.
Raises:
an error if this is not possible (graph is not valid). | polyaxon/pipelines/dags.py | def sort_topologically(dag):
"""Sort the dag breath first topologically.
Only the nodes inside the dag are returned, i.e. the nodes that are also keys.
Returns:
a topological ordering of the DAG.
Raises:
an error if this is not possible (graph is not valid).
"""
dag = copy.de... | def sort_topologically(dag):
"""Sort the dag breath first topologically.
Only the nodes inside the dag are returned, i.e. the nodes that are also keys.
Returns:
a topological ordering of the DAG.
Raises:
an error if this is not possible (graph is not valid).
"""
dag = copy.de... | [
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train | parse_negation_operation | Parse the negation modifier in an operation. | polyaxon/query/parser.py | def parse_negation_operation(operation: str) -> Tuple[bool, str]:
"""Parse the negation modifier in an operation."""
_operation = operation.strip()
if not _operation:
raise QueryParserException('Operation is not valid: {}'.format(operation))
negation = False
if _operation[0] == '~':
... | def parse_negation_operation(operation: str) -> Tuple[bool, str]:
"""Parse the negation modifier in an operation."""
_operation = operation.strip()
if not _operation:
raise QueryParserException('Operation is not valid: {}'.format(operation))
negation = False
if _operation[0] == '~':
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train | parse_comparison_operation | Parse the comparision operator in an operation. | polyaxon/query/parser.py | def parse_comparison_operation(operation: str) -> Tuple[Optional[str], str]:
"""Parse the comparision operator in an operation."""
_operation = operation.strip()
if not _operation:
raise QueryParserException('Operation is not valid: {}'.format(operation))
# Check inclusion comparison
if _ope... | def parse_comparison_operation(operation: str) -> Tuple[Optional[str], str]:
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_operation = operation.strip()
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raise QueryParserException('Operation is not valid: {}'.format(operation))
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train | parse_datetime_operation | Parse datetime operations.
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* negation single value: start_date:~2014-10-10
* interval: start_date:2010-10-10 10:10 .. 2012-10-10
* negation interval: start_date... | polyaxon/query/parser.py | def parse_datetime_operation(operation: str) -> 'QueryOpSpec':
"""Parse datetime operations.
A datetime operation can one of the following:
* single value: start_date:2014-10-10, start_date:>2014-10-10, start_date:>=2014-10-10
* negation single value: start_date:~2014-10-10
* interval: start_da... | def parse_datetime_operation(operation: str) -> 'QueryOpSpec':
"""Parse datetime operations.
A datetime operation can one of the following:
* single value: start_date:2014-10-10, start_date:>2014-10-10, start_date:>=2014-10-10
* negation single value: start_date:~2014-10-10
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train | parse_scalar_operation | Parse scalar operations.
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* negation single value: metric1:~1112, metric1:~<1112 equivalent to metric1:>=1112
This parser does not allow `|` and `..`. | polyaxon/query/parser.py | def parse_scalar_operation(operation: str) -> 'QueryOpSpec':
"""Parse scalar operations.
A scalar operation can one of the following:
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* negation single value: metric1:~1112, metric1:~<1112 equivalent to metric1:>=1112
This parser does... | def parse_scalar_operation(operation: str) -> 'QueryOpSpec':
"""Parse scalar operations.
A scalar operation can one of the following:
* single value: start_date:12, metric1:>0.9, metric1:>=-0.12
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train | parse_expression | Base parsing for expressions.
Every expression must follow a basic format:
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So this parser just split the expression into: field name, operation. | polyaxon/query/parser.py | def parse_expression(expression: str) -> Tuple[str, str]:
"""Base parsing for expressions.
Every expression must follow a basic format:
`name:[modifier|operator]operation[*[operator]operation]`
So this parser just split the expression into: field name, operation.
"""
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"""Base parsing for expressions.
Every expression must follow a basic format:
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So this parser just split the expression into: field name, operation.
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train | split_query | Split a query into different expressions.
Example:
name:bla, foo:<=1 | polyaxon/query/parser.py | def split_query(query: str) -> List[str]:
"""Split a query into different expressions.
Example:
name:bla, foo:<=1
"""
try:
_query = query.strip()
except (ValueError, AttributeError):
raise QueryParserException('query is not valid, received instead {}'.format(query))
exp... | def split_query(query: str) -> List[str]:
"""Split a query into different expressions.
Example:
name:bla, foo:<=1
"""
try:
_query = query.strip()
except (ValueError, AttributeError):
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train | tokenize_query | Tokenizes a standard search query in name: operations mapping.
Example:
moo:bla, foo:~<=1, foo:ll..ff
{
'moo': ['bla'],
'foo': ['~<=1', 'll..ff']
} | polyaxon/query/parser.py | def tokenize_query(query: str) -> Dict[str, Iterable]:
"""Tokenizes a standard search query in name: operations mapping.
Example:
moo:bla, foo:~<=1, foo:ll..ff
{
'moo': ['bla'],
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}
"""
expressions = split_query(query)
name_operat... | def tokenize_query(query: str) -> Dict[str, Iterable]:
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Example:
moo:bla, foo:~<=1, foo:ll..ff
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'moo': ['bla'],
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train | parse_field | Parses fields with underscores, and return field and suffix.
Example:
foo => foo, None
metric.foo => metric, foo | polyaxon/query/parser.py | def parse_field(field: str) -> Tuple[str, Optional[str]]:
"""Parses fields with underscores, and return field and suffix.
Example:
foo => foo, None
metric.foo => metric, foo
"""
_field = field.split('.')
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if len(_field) == 1 and _field[0]:
... | def parse_field(field: str) -> Tuple[str, Optional[str]]:
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Example:
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metric.foo => metric, foo
"""
_field = field.split('.')
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train | set_op_upstreams | Set the upstream operations for operation run. | polyaxon/pipelines/utils.py | def set_op_upstreams(op_run, op):
"""Set the upstream operations for operation run."""
# We get a list of all upstream ops or the current op
upstream_ops = op.upstream_operations.values_list('id', flat=True)
# We get latest op runs for the upstream_ops
latest_op_runs = OperationRun.objects.filter(id... | def set_op_upstreams(op_run, op):
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train | set_topological_dag_upstreams | Set the upstream runs for the operation runs in the dag following the topological sort. | polyaxon/pipelines/utils.py | def set_topological_dag_upstreams(dag, ops, op_runs, runs_by_ops):
"""Set the upstream runs for the operation runs in the dag following the topological sort."""
sorted_ops = dags.sort_topologically(dag=dag)
for op_id in sorted_ops:
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sorted_ops = dags.sort_topologically(dag=dag)
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train | create_pipeline_run | Create a pipeline run/instance. | polyaxon/pipelines/utils.py | def create_pipeline_run(pipeline, context_by_op):
"""Create a pipeline run/instance."""
pipeline_run = PipelineRun.objects.create(pipeline=pipeline)
dag, ops = pipeline.dag
# Go trough the operation and create operation runs and the upstreams
op_runs = {}
runs_by_ops = {}
for op_id in dag.ke... | def create_pipeline_run(pipeline, context_by_op):
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pipeline_run = PipelineRun.objects.create(pipeline=pipeline)
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train | k8s_events_handle_experiment_job_statuses | Experiment jobs statuses | polyaxon/k8s_events_handlers/tasks/statuses.py | def k8s_events_handle_experiment_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Experiment jobs statuses"""
details = payload['details']
job_uuid = details['labels']['job_uuid']
logger.debug('handling events status for job_uuid: %s, status: %s',
job_uuid, payload['stat... | def k8s_events_handle_experiment_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Experiment jobs statuses"""
details = payload['details']
job_uuid = details['labels']['job_uuid']
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train | k8s_events_handle_job_statuses | Project jobs statuses | polyaxon/k8s_events_handlers/tasks/statuses.py | def k8s_events_handle_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Project jobs statuses"""
details = payload['details']
job_uuid = details['labels']['job_uuid']
job_name = details['labels']['job_name']
project_name = details['labels'].get('project_name')
logger.debug('handli... | def k8s_events_handle_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Project jobs statuses"""
details = payload['details']
job_uuid = details['labels']['job_uuid']
job_name = details['labels']['job_name']
project_name = details['labels'].get('project_name')
logger.debug('handli... | [
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train | k8s_events_handle_plugin_job_statuses | Project Plugin jobs statuses | polyaxon/k8s_events_handlers/tasks/statuses.py | def k8s_events_handle_plugin_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Project Plugin jobs statuses"""
details = payload['details']
app = details['labels']['app']
job_uuid = details['labels']['job_uuid']
job_name = details['labels']['job_name']
project_name = details['labe... | def k8s_events_handle_plugin_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Project Plugin jobs statuses"""
details = payload['details']
app = details['labels']['app']
job_uuid = details['labels']['job_uuid']
job_name = details['labels']['job_name']
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train | k8s_events_handle_build_job_statuses | Project Plugin jobs statuses | polyaxon/k8s_events_handlers/tasks/statuses.py | def k8s_events_handle_build_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Project Plugin jobs statuses"""
details = payload['details']
app = details['labels']['app']
job_uuid = details['labels']['job_uuid']
job_name = details['labels']['job_name']
project_name = details['label... | def k8s_events_handle_build_job_statuses(self: 'celery_app.task', payload: Dict) -> None:
"""Project Plugin jobs statuses"""
details = payload['details']
app = details['labels']['app']
job_uuid = details['labels']['job_uuid']
job_name = details['labels']['job_name']
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train | get_sidecar_container | Return a pod sidecar container. | polyaxon/scheduler/spawners/templates/sidecars.py | def get_sidecar_container(job_container_name,
sidecar_container_name,
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sidecar_docker_image_pull_policy,
namespace,
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sidecar_arg... | def get_sidecar_container(job_container_name,
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train | ProtectedView.handle_exception | Use custom exception handler for errors. | polyaxon/api/utils/views/protected.py | def handle_exception(self, exc):
"""Use custom exception handler for errors."""
if isinstance(
exc, (rest_exceptions.NotAuthenticated,
rest_exceptions.AuthenticationFailed)) and self.HANDLE_UNAUTHENTICATED:
return HttpResponseRedirect('{}?next={}'.format(
... | def handle_exception(self, exc):
"""Use custom exception handler for errors."""
if isinstance(
exc, (rest_exceptions.NotAuthenticated,
rest_exceptions.AuthenticationFailed)) and self.HANDLE_UNAUTHENTICATED:
return HttpResponseRedirect('{}?next={}'.format(
... | [
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train | get_resources | Create resources requirements.
Args:
resources: `PodResourcesConfig`
Return:
`V1ResourceRequirements` | polyaxon/scheduler/spawners/templates/resources.py | def get_resources(resources): # pylint:disable=too-many-branches
"""Create resources requirements.
Args:
resources: `PodResourcesConfig`
Return:
`V1ResourceRequirements`
"""
limits = {}
requests = {}
if resources is None:
return None
if resources.cpu:
i... | def get_resources(resources): # pylint:disable=too-many-branches
"""Create resources requirements.
Args:
resources: `PodResourcesConfig`
Return:
`V1ResourceRequirements`
"""
limits = {}
requests = {}
if resources is None:
return None
if resources.cpu:
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train | has_project_permissions | This logic is extracted here to be used also with Sanic api. | polyaxon/scopes/permissions/projects.py | def has_project_permissions(user: 'User', project: 'Project', request_method: str) -> bool:
"""This logic is extracted here to be used also with Sanic api."""
# Superusers and the creator is allowed to do everything
if user.is_staff or user.is_superuser or project.user == user:
return True
# Ot... | def has_project_permissions(user: 'User', project: 'Project', request_method: str) -> bool:
"""This logic is extracted here to be used also with Sanic api."""
# Superusers and the creator is allowed to do everything
if user.is_staff or user.is_superuser or project.user == user:
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train | experiment_group_pre_delete | Delete all group outputs. | polyaxon/signals/deletion.py | def experiment_group_pre_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
if instance.is_selection:
return
# Delete outputs and logs
celery_app.send_task(
SchedulerCeleryTasks.STORES_SCHEDULE_OUTPUTS_DELETION,
kwargs={
'per... | def experiment_group_pre_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
if instance.is_selection:
return
# Delete outputs and logs
celery_app.send_task(
SchedulerCeleryTasks.STORES_SCHEDULE_OUTPUTS_DELETION,
kwargs={
'per... | [
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train | experiment_group_post_delete | Delete all group outputs. | polyaxon/signals/deletion.py | def experiment_group_post_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
auditor.record(event_type=EXPERIMENT_GROUP_DELETED, instance=instance)
remove_bookmarks(object_id=instance.id, content_type='experimentgroup') | def experiment_group_post_delete(sender, **kwargs):
"""Delete all group outputs."""
instance = kwargs['instance']
auditor.record(event_type=EXPERIMENT_GROUP_DELETED, instance=instance)
remove_bookmarks(object_id=instance.id, content_type='experimentgroup') | [
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train | get_asset_url | Return a static asset URL (located within Polyaxon's static files).
Example:
```python
>>> get_asset_url('polyaxon', 'dist/global.css')
... "/_static/74d127b78dc7daf2c51f/polyaxon/dist/global.css"
``` | polyaxon/libs/statics.py | def get_asset_url(module: str, path: str) -> str:
"""Return a static asset URL (located within Polyaxon's static files).
Example:
```python
>>> get_asset_url('polyaxon', 'dist/global.css')
... "/_static/74d127b78dc7daf2c51f/polyaxon/dist/global.css"
```
"""
return '{}/{}... | def get_asset_url(module: str, path: str) -> str:
"""Return a static asset URL (located within Polyaxon's static files).
Example:
```python
>>> get_asset_url('polyaxon', 'dist/global.css')
... "/_static/74d127b78dc7daf2c51f/polyaxon/dist/global.css"
```
"""
return '{}/{}... | [
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train | ResourceManager.get_init_container | Pod init container for setting outputs path. | polyaxon/scheduler/spawners/templates/jobs/manager.py | def get_init_container(self,
init_command,
init_args,
env_vars,
context_mounts,
persistence_outputs,
persistence_data):
"""Pod init container for sett... | def get_init_container(self,
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train | ResourceManager.get_init_container | Pod init container for setting outputs path. | polyaxon/scheduler/spawners/templates/dockerizers/manager.py | def get_init_container(self,
init_command,
init_args,
env_vars,
context_mounts,
persistence_outputs,
persistence_data):
"""Pod init container for sett... | def get_init_container(self,
init_command,
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env_vars,
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train | BaseIterationManager.create_iteration | Create an iteration for the experiment group (works for grid and random). | polyaxon/hpsearch/iteration_managers/base.py | def create_iteration(self, num_suggestions):
"""Create an iteration for the experiment group (works for grid and random)."""
from db.models.experiment_groups import ExperimentGroupIteration
iteration_config = BaseIterationConfig(iteration=0,
num_su... | def create_iteration(self, num_suggestions):
"""Create an iteration for the experiment group (works for grid and random)."""
from db.models.experiment_groups import ExperimentGroupIteration
iteration_config = BaseIterationConfig(iteration=0,
num_su... | [
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train | BaseIterationManager.update_iteration | Update the last experiment group's iteration with experiment performance. | polyaxon/hpsearch/iteration_managers/base.py | def update_iteration(self):
"""Update the last experiment group's iteration with experiment performance."""
iteration_config = self.get_iteration_config()
if not iteration_config:
return
experiments_metrics = self.experiment_group.get_experiments_metrics(
experime... | def update_iteration(self):
"""Update the last experiment group's iteration with experiment performance."""
iteration_config = self.get_iteration_config()
if not iteration_config:
return
experiments_metrics = self.experiment_group.get_experiments_metrics(
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train | BaseIterationManager.update_iteration_num_suggestions | Update iteration's num_suggestions. | polyaxon/hpsearch/iteration_managers/base.py | def update_iteration_num_suggestions(self, num_suggestions):
"""Update iteration's num_suggestions."""
iteration_config = self.experiment_group.iteration_config
iteration_config.num_suggestions = num_suggestions
self._update_config(iteration_config) | def update_iteration_num_suggestions(self, num_suggestions):
"""Update iteration's num_suggestions."""
iteration_config = self.experiment_group.iteration_config
iteration_config.num_suggestions = num_suggestions
self._update_config(iteration_config) | [
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train | ExperimentCreateSerializer.validate_config | We only validate the config if passed.
Also we use the ExperimentSpecification to check if this config was
intended as an experiment. | polyaxon/api/experiments/serializers.py | def validate_config(self, config):
"""We only validate the config if passed.
Also we use the ExperimentSpecification to check if this config was
intended as an experiment.
"""
# config is optional
if not config:
return config
spec = validate_experime... | def validate_config(self, config):
"""We only validate the config if passed.
Also we use the ExperimentSpecification to check if this config was
intended as an experiment.
"""
# config is optional
if not config:
return config
spec = validate_experime... | [
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train | Event.get_event_action | Return the second part of the event_type
e.g.
>>> Event.event_type = 'experiment.deleted'
>>> Event.get_event_action() == 'deleted' | polyaxon/event_manager/event.py | def get_event_action(cls) -> Optional[str]:
"""Return the second part of the event_type
e.g.
>>> Event.event_type = 'experiment.deleted'
>>> Event.get_event_action() == 'deleted'
"""
if not cls.actor:
return None
return event_context.get_event_action... | def get_event_action(cls) -> Optional[str]:
"""Return the second part of the event_type
e.g.
>>> Event.event_type = 'experiment.deleted'
>>> Event.get_event_action() == 'deleted'
"""
if not cls.actor:
return None
return event_context.get_event_action... | [
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train | create_build_job | Get or Create a build job based on the params.
If a build job already exists, then we check if the build has already an image created.
If the image does not exists, and the job is already done we force create a new job.
Returns:
tuple: (build_job, image_exists[bool], build_status[bool]) | polyaxon/scheduler/dockerizer_scheduler.py | def create_build_job(user, project, config, code_reference, configmap_refs=None, secret_refs=None):
"""Get or Create a build job based on the params.
If a build job already exists, then we check if the build has already an image created.
If the image does not exists, and the job is already done we force cr... | def create_build_job(user, project, config, code_reference, configmap_refs=None, secret_refs=None):
"""Get or Create a build job based on the params.
If a build job already exists, then we check if the build has already an image created.
If the image does not exists, and the job is already done we force cr... | [
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train | scan | Scan a YAML stream and produce scanning tokens. | lib/yaml/__init__.py | def scan(stream, Loader=Loader):
"""
Scan a YAML stream and produce scanning tokens.
"""
loader = Loader(stream)
try:
while loader.check_token():
yield loader.get_token()
finally:
loader.dispose() | def scan(stream, Loader=Loader):
"""
Scan a YAML stream and produce scanning tokens.
"""
loader = Loader(stream)
try:
while loader.check_token():
yield loader.get_token()
finally:
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train | parse | Parse a YAML stream and produce parsing events. | lib/yaml/__init__.py | def parse(stream, Loader=Loader):
"""
Parse a YAML stream and produce parsing events.
"""
loader = Loader(stream)
try:
while loader.check_event():
yield loader.get_event()
finally:
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"""
Parse a YAML stream and produce parsing events.
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try:
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yield loader.get_event()
finally:
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train | compose | Parse the first YAML document in a stream
and produce the corresponding representation tree. | lib/yaml/__init__.py | def compose(stream, Loader=Loader):
"""
Parse the first YAML document in a stream
and produce the corresponding representation tree.
"""
loader = Loader(stream)
try:
return loader.get_single_node()
finally:
loader.dispose() | def compose(stream, Loader=Loader):
"""
Parse the first YAML document in a stream
and produce the corresponding representation tree.
"""
loader = Loader(stream)
try:
return loader.get_single_node()
finally:
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train | compose_all | Parse all YAML documents in a stream
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"""
Parse all YAML documents in a stream
and produce corresponding representation trees.
"""
loader = Loader(stream)
try:
while loader.check_node():
yield loader.get_node()
finally:
loader.dispose() | def compose_all(stream, Loader=Loader):
"""
Parse all YAML documents in a stream
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"""
loader = Loader(stream)
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while loader.check_node():
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train | load | Parse the first YAML document in a stream
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"""
Parse the first YAML document in a stream
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train | load_all | Parse all YAML documents in a stream
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"""
Parse all YAML documents in a stream
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load_warning('load_all')
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load_warning('load_all')
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train | emit | Emit YAML parsing events into a stream.
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"""
Emit YAML parsing events into a stream.
If stream is None, return the produced string instead.
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getvalue = None
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"""
Emit YAML parsing events into a stream.
If stream is None, return the produced string instead.
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getvalue = None
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train | serialize | Serialize a representation tree into a YAML stream.
If stream is None, return the produced string instead. | lib/yaml/__init__.py | def serialize(node, stream=None, Dumper=Dumper, **kwds):
"""
Serialize a representation tree into a YAML stream.
If stream is None, return the produced string instead.
"""
return serialize_all([node], stream, Dumper=Dumper, **kwds) | def serialize(node, stream=None, Dumper=Dumper, **kwds):
"""
Serialize a representation tree into a YAML stream.
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"""
return serialize_all([node], stream, Dumper=Dumper, **kwds) | [
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train | dump | Serialize a Python object into a YAML stream.
If stream is None, return the produced string instead. | lib/yaml/__init__.py | def dump(data, stream=None, Dumper=Dumper, **kwds):
"""
Serialize a Python object into a YAML stream.
If stream is None, return the produced string instead.
"""
return dump_all([data], stream, Dumper=Dumper, **kwds) | def dump(data, stream=None, Dumper=Dumper, **kwds):
"""
Serialize a Python object into a YAML stream.
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train | safe_dump_all | Serialize a sequence of Python objects into a YAML stream.
Produce only basic YAML tags.
If stream is None, return the produced string instead. | lib/yaml/__init__.py | def safe_dump_all(documents, stream=None, **kwds):
"""
Serialize a sequence of Python objects into a YAML stream.
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If stream is None, return the produced string instead.
"""
return dump_all(documents, stream, Dumper=SafeDumper, **kwds) | def safe_dump_all(documents, stream=None, **kwds):
"""
Serialize a sequence of Python objects into a YAML stream.
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return dump_all(documents, stream, Dumper=SafeDumper, **kwds) | [
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train | safe_dump | Serialize a Python object into a YAML stream.
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"""
Serialize a Python object into a YAML stream.
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"""
return dump_all([data], stream, Dumper=SafeDumper, **kwds) | def safe_dump(data, stream=None, **kwds):
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Serialize a Python object into a YAML stream.
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train | add_implicit_resolver | Add an implicit scalar detector.
If an implicit scalar value matches the given regexp,
the corresponding tag is assigned to the scalar.
first is a sequence of possible initial characters or None. | lib/yaml/__init__.py | def add_implicit_resolver(tag, regexp, first=None,
Loader=Loader, Dumper=Dumper):
"""
Add an implicit scalar detector.
If an implicit scalar value matches the given regexp,
the corresponding tag is assigned to the scalar.
first is a sequence of possible initial characters or None.
"""
... | def add_implicit_resolver(tag, regexp, first=None,
Loader=Loader, Dumper=Dumper):
"""
Add an implicit scalar detector.
If an implicit scalar value matches the given regexp,
the corresponding tag is assigned to the scalar.
first is a sequence of possible initial characters or None.
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train | add_path_resolver | Add a path based resolver for the given tag.
A path is a list of keys that forms a path
to a node in the representation tree.
Keys can be string values, integers, or None. | lib/yaml/__init__.py | def add_path_resolver(tag, path, kind=None, Loader=Loader, Dumper=Dumper):
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Add a path based resolver for the given tag.
A path is a list of keys that forms a path
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Add a path based resolver for the given tag.
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train | YAMLObject.to_yaml | Convert a Python object to a representation node. | lib/yaml/__init__.py | def to_yaml(cls, dumper, data):
"""
Convert a Python object to a representation node.
"""
return dumper.represent_yaml_object(cls.yaml_tag, data, cls,
flow_style=cls.yaml_flow_style) | def to_yaml(cls, dumper, data):
"""
Convert a Python object to a representation node.
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return dumper.represent_yaml_object(cls.yaml_tag, data, cls,
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train | serialize_all | Serialize a sequence of representation trees into a YAML stream.
If stream is None, return the produced string instead. | lib3/yaml/__init__.py | def serialize_all(nodes, stream=None, Dumper=Dumper,
canonical=None, indent=None, width=None,
allow_unicode=None, line_break=None,
encoding=None, explicit_start=None, explicit_end=None,
version=None, tags=None):
"""
Serialize a sequence of representation trees into a YAML stream.... | def serialize_all(nodes, stream=None, Dumper=Dumper,
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encoding=None, explicit_start=None, explicit_end=None,
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train | something | Do not produce empty tokens. | examples/pygments-lexer/yaml.py | def something(TokenClass):
"""Do not produce empty tokens."""
def callback(lexer, match, context):
text = match.group()
if not text:
return
yield match.start(), TokenClass, text
context.pos = match.end()
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yield match.start(), TokenClass, text
context.pos = match.end()
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train | set_indent | Set the previously saved indentation level. | examples/pygments-lexer/yaml.py | def set_indent(TokenClass, implicit=False):
"""Set the previously saved indentation level."""
def callback(lexer, match, context):
text = match.group()
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".... | e471e86bf6dabdad45a1438c20a4a5c033eb9034 |
train | parse_block_scalar_empty_line | Process an empty line in a block scalar. | examples/pygments-lexer/yaml.py | def parse_block_scalar_empty_line(IndentTokenClass, ContentTokenClass):
"""Process an empty line in a block scalar."""
def callback(lexer, match, context):
text = match.group()
if (context.block_scalar_indent is None or
len(text) <= context.block_scalar_indent):
if te... | def parse_block_scalar_empty_line(IndentTokenClass, ContentTokenClass):
"""Process an empty line in a block scalar."""
def callback(lexer, match, context):
text = match.group()
if (context.block_scalar_indent is None or
len(text) <= context.block_scalar_indent):
if te... | [
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"scalar",
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] | yaml/pyyaml | python | https://github.com/yaml/pyyaml/blob/e471e86bf6dabdad45a1438c20a4a5c033eb9034/examples/pygments-lexer/yaml.py#L106-L121 | [
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train | parse_plain_scalar_indent | Process indentation spaces in a plain scalar. | examples/pygments-lexer/yaml.py | def parse_plain_scalar_indent(TokenClass):
"""Process indentation spaces in a plain scalar."""
def callback(lexer, match, context):
text = match.group()
if len(text) <= context.indent:
context.stack.pop()
context.stack.pop()
return
if text:
... | def parse_plain_scalar_indent(TokenClass):
"""Process indentation spaces in a plain scalar."""
def callback(lexer, match, context):
text = match.group()
if len(text) <= context.indent:
context.stack.pop()
context.stack.pop()
return
if text:
... | [
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... | e471e86bf6dabdad45a1438c20a4a5c033eb9034 |
train | score | Collocation score | wordcloud/tokenization.py | def score(count_bigram, count1, count2, n_words):
"""Collocation score"""
if n_words <= count1 or n_words <= count2:
# only one words appears in the whole document
return 0
N = n_words
c12 = count_bigram
c1 = count1
c2 = count2
p = c2 / N
p1 = c12 / c1
p2 = (c2 - c12)... | def score(count_bigram, count1, count2, n_words):
"""Collocation score"""
if n_words <= count1 or n_words <= count2:
# only one words appears in the whole document
return 0
N = n_words
c12 = count_bigram
c1 = count1
c2 = count2
p = c2 / N
p1 = c12 / c1
p2 = (c2 - c12)... | [
"Collocation",
"score"
] | amueller/word_cloud | python | https://github.com/amueller/word_cloud/blob/d36f526e3d8346e6d7a2656631f05f68e402517d/wordcloud/tokenization.py#L14-L28 | [
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train | process_tokens | Normalize cases and remove plurals.
Each word is represented by the most common case.
If a word appears with an "s" on the end and without an "s" on the end,
the version with "s" is assumed to be a plural and merged with the
version without "s" (except if the word ends with "ss").
Parameters
-... | wordcloud/tokenization.py | def process_tokens(words, normalize_plurals=True):
"""Normalize cases and remove plurals.
Each word is represented by the most common case.
If a word appears with an "s" on the end and without an "s" on the end,
the version with "s" is assumed to be a plural and merged with the
version without "s" ... | def process_tokens(words, normalize_plurals=True):
"""Normalize cases and remove plurals.
Each word is represented by the most common case.
If a word appears with an "s" on the end and without an "s" on the end,
the version with "s" is assumed to be a plural and merged with the
version without "s" ... | [
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] | amueller/word_cloud | python | https://github.com/amueller/word_cloud/blob/d36f526e3d8346e6d7a2656631f05f68e402517d/wordcloud/tokenization.py#L74-L137 | [
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train | GroupedColorFunc.get_color_func | Returns a single_color_func associated with the word | examples/colored_by_group.py | def get_color_func(self, word):
"""Returns a single_color_func associated with the word"""
try:
color_func = next(
color_func for (color_func, words) in self.color_func_to_words
if word in words)
except StopIteration:
color_func = self.defa... | def get_color_func(self, word):
"""Returns a single_color_func associated with the word"""
try:
color_func = next(
color_func for (color_func, words) in self.color_func_to_words
if word in words)
except StopIteration:
color_func = self.defa... | [
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"Sto... | d36f526e3d8346e6d7a2656631f05f68e402517d |
train | random_color_func | Random hue color generation.
Default coloring method. This just picks a random hue with value 80% and
lumination 50%.
Parameters
----------
word, font_size, position, orientation : ignored.
random_state : random.Random object or None, (default=None)
If a random object is given, this ... | wordcloud/wordcloud.py | def random_color_func(word=None, font_size=None, position=None,
orientation=None, font_path=None, random_state=None):
"""Random hue color generation.
Default coloring method. This just picks a random hue with value 80% and
lumination 50%.
Parameters
----------
word, font_... | def random_color_func(word=None, font_size=None, position=None,
orientation=None, font_path=None, random_state=None):
"""Random hue color generation.
Default coloring method. This just picks a random hue with value 80% and
lumination 50%.
Parameters
----------
word, font_... | [
"Random",
"hue",
"color",
"generation",
"."
] | amueller/word_cloud | python | https://github.com/amueller/word_cloud/blob/d36f526e3d8346e6d7a2656631f05f68e402517d/wordcloud/wordcloud.py#L66-L84 | [
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"No... | d36f526e3d8346e6d7a2656631f05f68e402517d |
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